Top Performing Marketing Campaign Types for Ecommerce
TL;DR
- Start with high-intent traffic and owned channels. Search, branded campaigns, and lifecycle email deliver the most reliable ROAS for most stores.
- Meta and TikTok scale fast when creative is refreshed weekly and you separate prospecting vs. remarketing.
- Automate lifecycle: welcome, browse abandon, cart abandon, post-purchase, win-back. These flows are usually your highest-ROI sends.
- Measure on blended MER and contribution margin, not just platform ROAS. Use post-purchase surveys and server-side tracking to close gaps.
- Common mistakes: turning off branded search, mixing prospecting and remarketing, under-investing in creative testing, ignoring LTV and contribution margin.
What do we mean by "campaign type"?
A campaign type is a channel plus objective and audience strategy that reliably maps to a business outcome. Think "Google Branded Search," "Meta Broad Prospecting," or "Email Cart Abandon" rather than just "Google" or "Email."
How to evaluate performance
- Intent: How close to purchase the user is
- Scale: How much spend you can profitably push
- Control: Targeting and creative levers available
- Payback: Time to recover CAC
- Effort: Creative, ops, and data work required
Top performing ecommerce campaign types
1) Google Search - Branded and High-Intent Non-Brand
Why it works: Captures demand with clear purchase intent
Setup
- Separate branded vs. non-brand
- Exact match for branded; SKAGs or tight ad groups for key non-brand terms
- Use ad extensions and price annotations
Benchmarks
- Branded ROAS: 600%+ is common for DTC with healthy demand
- Non-brand ROAS: 150-350% depending on AOV and competition
Do's
- Always protect branded terms
- Send to best converting PDP or curated LP
Don'ts
- Mix brand and non-brand in one campaign
- Optimize only to clicks; watch profit and MER
2) Google Performance Max (PMax) for Shopping
Why it works: Scales Shopping inventory with automation
Setup
- Clean product feed with titles, attributes, GTINs, image guidelines
- Split high-margin or hero SKUs into their own asset groups
- Layer audience signals but let automation learn
Benchmarks
- ROAS: 200-400% for many stores after 2-4 weeks of learning
Do's
- Keep excluding unprofitable products
- Feed health reviews weekly
Don'ts
- Starve PMax during learning
- Use one catch-all asset group for all products
3) Meta (Facebook/Instagram) - Broad Prospecting + Remarketing
Why it works: Unmatched scale for discovery when creative is strong
Setup
- Prospecting: 1-3 broad ad sets, Advantage+ placements, multiple hooks
- Remarketing: 3-10 day and 11-30 day viewers/cart abandoners
- Creative: UGC, founders' talk, comparisons, demos, social proof
Benchmarks
- Prospecting ROAS: 100-250%
- Remarketing ROAS: 300-700%
Do's
- Refresh creatives weekly, test hooks and angles
- Use product-level page rules for DPA
Don'ts
- Combine prospecting and remarketing in one ad set
- Judge in 48 hours; use 7-day view with contribution margin
4) TikTok - Spark Ads and Creator Whitelisting
Why it works: Low CPMs and thumb-stopping creative
Setup
- Spark Ads from creators and customer posts
- Test 10+ hooks per product. Short, fast cuts.
- Send to mobile-optimized PDP or quiz LP
Benchmarks
- Prospecting ROAS: 80-200% early; better as LTV accrues
Do's
- Creative testing cadence weekly
- Use influencer seeding to keep UGC fresh
Don'ts
- Repurpose static IG assets directly
- Optimize without proper UTMs and post-purchase survey
5) Lifecycle Email (Klaviyo, Customer.io)
Why it works: Owned, high-margin revenue with strong intent triggers
Core flows
- Welcome series with offer or value exchange
- Browse abandon and cart abandon
- Post-purchase cross-sell and review request
- 60-90 day win-back
Benchmarks
- 20-35% of monthly revenue from email for healthy programs
Do's
- Segment by engagement and predicted CLV
- Test subject lines, offers, and send times
Don'ts
- Batch-and-blast to your full list
- Neglect deliverability and list hygiene
6) SMS
Why it works: High visibility for urgent or cart-adjacent messages
Use cases: Cart recovery, shipping updates, limited drops
Do's: Explicit consent, tight frequency caps, value-led messages
Don'ts: Treat like email. Avoid long texts and daily promos
7) Affiliate and Influencer Programs
Why it works: Pay for performance and social proof
Setup: Tiered commissions, unique codes, dedicated LPs, creator briefs
Do's: Track by code and link, pay fast, repurpose winning content in paid
Don'ts: One-off posts with no tracking or content rights
Budget allocation by stage
Launch or early scale
- 30–40% Search and PMax
- 30–40% Meta prospecting
- 10–20% Remarketing across Meta and Google
- 10% TikTok testing
- Email and SMS flows always on
Mature stores
- Keep brand search and lifecycle on
- Shift incremental testing into creative and new audiences
Measurement and attribution
- Use blended MER and contribution margin as your north star
- Implement server-side tracking and conversions APIs
- Add "How did you hear about us?" on checkout for qualitative signals
- Compare platform ROAS with modeled performance in your analytics stack
Examples
Example AOV $60 consumable brand
- Branded search and email flows drive 40% of revenue
- Meta prospecting breaks even within 7 days, profitable by day 30
Example AOV $180 durable product
- PMax + non-brand search carry scale
- TikTok creators supply new angles for Meta and PMax assets
Do's and Don'ts recap
Do
- Separate prospecting and remarketing
- Refresh creatives weekly
- Protect branded search
- Track on MER and contribution margin
Don't
- Mix intent levels in one campaign
- Judge channels in 48 hours
- Ignore lifecycle programs
- Scale without feed and site hygiene
Utilize your data
Subtle note from us at Karbon Analytics: we turn your store and marketing data into AI-generated action plans. Connect sources like Google Analytics, Meta Ads, and Shopify, and we'll surface a prioritized set of experiments, budget shifts, and feed or creative fixes tailored to your products and margins.
What this looks like in practice
- "Increase PMax budget by 15% on high-margin SKUs with >3.0 ROAS over 14 days"
- "Spin a new UGC angle for TikTok focused on unboxing benefits. Test 5 hooks."
- "Restore branded search coverage; CPCs rising and impression share <80%."
Why it's useful
- Keeps the playbooks above grounded in your actual performance data
- Helps smaller teams operate like larger ones without adding headcount
If you want to keep this purely educational, skip this and use the checklists above. When you're ready to operationalize, take a look at Karbon Analytics.